Distortions to Agricultural Incentives: introduction to a World Bank research project Kym Anderson Development Research Group, World Bank Global Forum on Agriculture OECD, Paris, 20-21 November 2006 Views expressed are the authors alone and not necessarily those of the World Bank, its Executive directors, or its institutional funders
Aim of the research project To expand the empirical evidence on the changing extent, causes and effects of distortions to the world s agricultural markets over the past 50 years financed mainly by donor Trust Funds for research at the World Bank, but also in collaboration with FAO, IFPRI, OECD and USDA (none of whom bear any responsibility for our findings and their interpretation!)
Structure of research project Stage 1 (2006): Country case studies to provide time series of the extent of distortions and an analytical narrative explaining the evolution of policies leading potentially to 4 regional volumes plus a global book Stage 2 (2007+): More-intensive empirical analysis across countries and over time of causes and effects (on growth, farm incomes, inequality, poverty, etc.) of chosen vs. alternative policies, retrospectively and prospectively
Why undertake this project now? 20 years since the and Anderson and Hayami (1986) and Krueger, Schiff and Valdes (1988) time series finished, and much has changed since then: in policies, including dramatic reforms in our capacity to analyze the reasons behind, and the extent and effects of, those interventions and reforms Client govts and hence operational parts of the World Bank want this detailed understanding in order to fine-tune their views on optimal strategies for unilateral reform by developing countries for preferential and multilateral reforms for sustainable development and poverty alleviation Next year s World Development Report 2008 is focusing on agriculture (first time since 1986)
Why the issue is important More than two-thirds of the world s poor live in developing countries (DCs) and depend directly or indirectly on agriculture for their livelihood Govt policies, in the past at least, have depressed farm incomes in DCs Anti-agric policies in DCs themselves (K/S/V study) Pro-agric policies in high-income countries (HICs), which lower int l food prices and thereby (at least some) key farmgate prices in DCs The policy instruments chosen, in either DCs or HICs, are not the most efficient for achieving governments stated objectives especially the alleviation of inequality and poverty
Some unresolved questions Is it still true today that policies depress DC farm incomes, given the various reforms since the 1980s by them and HICs? Specifically, to what extent have: DCs reduced their anti-trade bias? DCs reduced their anti-agricultural production bias and pro-urban consumption (and investment) bias? Some MICs become agricultural protectionists? HICs re-instrumented their support programs (and provided non-reciprocal preferences) so as to make them depress farm household incomes in DCs less?
What defines a distortion? Bhagwati (1971), Corden (1974): Any trade tax/subsidy/qr/dual exchange rate system except where one has sustainable monopoly power in an int l market, e.g. vanilla for Madagascar(?) Any producer or consumer price tax/subsidy/qr on outputs, productive factors or intermediate inputs, or VAT/GST except where it directly overcomes an externality or is set optimally across all products or factors to raise govt revenue Any differential rates of income or capital gains tax again, except where needed to satisfy society s redistributive goals optimally For this project: the focus is on just those measures that can be changed by the stroke of legislators pen Not to be confused with price wedges due to trade costs, imperfect competition in the value chain, etc.
Initial post-colonial years to mid-1980s In developing countries (and ANZ), importsubstituting industrialization was pursued, generating anti-trade, anti-agricultural biases and artificially lowering urban food prices in DCs while in industrial market economies (other than ANZ), farmers received steadily rising transfers from taxpayers and urban consumers initially with an anti-trade bias, but supplemented in the 1980s with agric export subsidies
Nominal rate of agric assistance, 1980-82 (from Tyers and Anderson 1986, for the World Bank s WDR)
Nominal rate of agric assistance, 1980-82 (from Tyers and Anderson 1986) NRA f = 0.22 + 0.11 YPC 0.51 CA A R 2 = 0.83 (5.6) (-10.7)
Total rate of agric assistance, %, 1960-84 (from Krueger/Schiff/Valdes 1988) Income group (lowest first): Group 1 Importables -11 Exportables -49 Group II Group III Group IV All DCs -13-2 15-9 -40-14 -1-35
Krueger/Schiff/Valdes Found direct agricultural taxes were less important than the negative indirect effects on agric incentives of manufacturing protection and overvalued exchange rates
What s happened in DCs since mid-1980s? Indicators of reductions in disincentives for DC farmers: Less-distorted foreign exchange markets although that fall in the black market premium helps all tradables sectors Decline in tariffs, and by more for non-agric than for agric Declines in use of explicit export taxes although implicit restraints still exist (& explicit ones added in Argentina), so anti-trade bias continues
Weighted average black market foreign exchange rate premia (%) 1960s 1970s 1980s 1991-3 Africa 23 45 75 23 South & East Asia 233 25 15 6 E. Europe & Central Asia 277 231 238 5 Latin America & Carib 13 34 89 9 All dev. countries 144 77 76 9
Facts to explain Extreme reluctance of high-income countries to make major cuts agric protection, even though protection to non-ag is now close to zero with notable exceptions of Au & NZ, which have brought both close to zero (as also in Chile) Move by DCs first to assist manuf at expense of primary products after independence in early 1960s, but since the 1980s many have begun reducing agric disincentives for example, Uganda
Total rate of agric assistance, Uganda, 1961 to 2004 (from Matthews, Claquin & Opolot 2006) 0.6 Post-Independence Collapse Recovery Post-liberalization 0.4 0.2 0.0-0.2-0.4-0.6 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 NRA non-agriculture DRA agriculture TRA agriculture
NRAs, agric vs. nonag tradables, NZ 0.4 0.3 0.2 NRA Ag Tradables NRA NonAg Trad RAI Agric 0.1 0-0.1 1965-69 1970-74 1975-79 1980-84 1985-89 1990-94 1995-99 2000-05 -0.2-0.3
Relative Assistance Index (RAI) Defined as the proportional change, due to agric and non-ag policies, in the relative price of agric tradables: RAI = [(1+NRA a )/(1+NRA na )] 1 or NAC a /NAC na 1
Important to separate import-competing from exportable industries Because the average might be close to zero yet each of the two sub-sectors are highly distorted for example, Ghana And because there might be dual exchange rates (without or with retention schemes) that implicitly tax both exports and imports (so harming export industries but helping import-competing industries) for example, China
NRAs for agric, Ghana, 1961-2004 (from Brooks, Croppenstedt and Aggrey-Fynn 2006) 0.8 0.6 0.4 0.2 0.0 Importable Exportable Total -0.2-0.4-0.6 1955-1957 1958-1982 1984-1992 1993-1998 1999-2004
10 0-10 -20-30 -40-50 NRA for rice, China, 1981 to 2004 (from Huang, Martin and Rozelle 2006) Rice NRA-official NRA- eqm 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 1981
Value added beyond K/S/V Longer time period Two more decades of annual data for their 18 DCs Larger sample of countries Another 20+ DCs, plus ECA transition economies and HICs (representing >90% of global GDP and agriculture) Broader primary agric product coverage (70+%) Separate coverage of lightly processed food Use of new methodological developments for CGE and econometric analyses of causes and effects of policies in Stage 2 of project, including for analyzing inequality and poverty impacts of own and other-countries policies
Value added beyond OECD s PSEs PSEs/CSEs are a wonderful springboard for OECD and Europe s transition economies and now also Brazil, China, South Africa But we need to go back before 1986 to see full post-war policy evolution in HICs And to calculate for a wider range of DCs over a longer period to see evolution since independence Need also to distinguish lightly processed from primary products (necessary for CGE analysis), to better examine pass-though back down the value chain to the farm gate Is a low farm-gate price due to an export tax, to high domestic trade costs, or to rent extraction by monopoly processor?
Time period coverage For K/S/V and Anderson/Hayami countries, from the start of their time period (which ranged from 1955 to 1964) For transition countries, from start of transition (1991 for ECA, a decade earlier for China) For others, as far back to 1955 as possible
Country coverage ECA (18): EU8, Bu&Ro, Ru, Tu, Ka, Ky, Uk, 3CAs LAC (8): Ar, Br, Ch, Co, DR, Ec, Mx, Ni Asia (13): Ba, Ch, Id, In, Ko, Ma, Pa, Ph, SL, Ta, Th, Vn Africa (22): Ca, Cd I, Eg, Eth, Gh, Ke, Ma, Mor, Moz, Ni, Se, SA, Su, Ta, Ug, Za, Zi, Cotton-5 (Be, BF, Ch, Ma, To) HICs (21): Au, Ca, EFTA, EU15, Ja, NZ, US
For further details See www.worldbank.org/agdistortions Email me at kanderson@worldbank.org